Instructions to use varcoder/CrackSeg-MIT-b0-dice with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use varcoder/CrackSeg-MIT-b0-dice with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, SegformerForSemanticSegmentation processor = AutoImageProcessor.from_pretrained("varcoder/CrackSeg-MIT-b0-dice") model = SegformerForSemanticSegmentation.from_pretrained("varcoder/CrackSeg-MIT-b0-dice", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 1700
Browse files- pytorch_model.bin +1 -1
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 109529789
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:a0f229a9e072626a1b6de3827d46e9e4c9fd5b9d7c1076d1ae93ff5b3e7a9a02
|
| 3 |
size 109529789
|